By Paul Gendreau and Claire Goggin, Centre for Criminal Justice Studies,
University of New Brunswick, and Francis T. Cullen, Department of Criminal
Justice, University of Cincinnati

The views expressed are those of the authors and do not necessarily reflect
the views of the Department of the Solicitor General Canada. This document is
available in French. Ce rapport est disponible en français sous le titre: L'incidence
de l'emprisonnement sur la récidive.

The use of prisons to control crime has increased in frequency in the last
decade. Most recently, mandatory minimum sentencing policies have gained
widespread popularity throughout the United States, severely limiting judicial
discretion in sentencing. The principle rationale for mandatory minimums is the
belief that length of time in prison acts as a deterrent to future recidivism.

Three schools of thought dominate the area. The first is that prisons
definitely suppress criminal behaviour. Given the unpleasantness of prison life
and the negative social stigma associated with incarceration, these should serve
as deterrents to later criminal behaviour. The second, the "schools of
crime" viewpoint, proposes just the opposite, that is, that prisons
increase criminality. By this account, the barren, inhumane, and psychologically
destructive nature of prisonisation makes offenders more likely to recidivate
upon release. The third school of thought, which we label the
"minimalist/interaction" position, contends that the effect of prison
on offenders is, for the most part, minimal. This view states that prisons are
essentially "psychological deep freezes", in that offenders enter
prison with a set of antisocial attitudes and behaviours which are little
changed during incarceration. This perspective also suggests that lower risk
offenders may be more adversely affected by greater lengths of incarceration
through exposure to an environment typically dominated by their higher risk,
more hard core peers.

Fifty studies dating from 1958 involving 336,052 offenders produced 325
correlations between recidivism and (a) length of time in prison and recidivism
or (b) serving a prison sentence vs. receiving a community-based sanction. The
data was analysed using quantitative methods (i.e., meta-analysis) to determine
whether prison reduced criminal behaviour or recidivism.

The results were as follows: under both of the above conditions, prison
produced slight increases in recidivism. Secondly, there was some tendency for
lower risk offenders to be more negatively affected by the prison experience.

The essential conclusions reached from this study were:

1. Prisons should not be used with the expectation of reducing criminal
behaviour.

2. On the basis of the present results, excessive use of incarceration has
enormous cost implications.

3. In order to determine who is being adversely affected by prison, it is
incumbent upon prison officials to implement repeated, comprehensive assessments
of offenders’ attitudes, values, and behaviours while incarcerated.

4. The primary justification of prison should be to incapacitate offenders
(particularly, those of a chronic, higher risk nature) for reasonable periods
and to exact retribution.

Introduction

The application of sanctions by the legal system has been at the forefront of
society’s efforts to control criminal behaviour. The most recent trend,
especially in the U.S., has been to use prison sentences, particularly what are
known as mandatory sentences, to achieve this goal. Mandatory sentences are
grid-like sentencing prescriptions that attempt to make the

"punishment" fit the crime. Judicial discretion is severely limited
as regards weighting of individual circumstances in sentencing. Almost all U.S.
states and the federal government have some sort of mandatory laws, wherein drug
crimes have figured prominently.

California has been a leader in this area as the proponent of one of the
broadest, toughest and most rigorously applied mandatory minimum policies,
commonly known as the "three strikes and out" law (Stolzenberg & D’Alessio,
1997). The state provides a mandatory sentence of 25 years to life for a third
felony and there is no distinction among types of felonies. To illustrate how
harsh mandatory sentences can be, consider one Greg Taylor (Bellisle, 1999),
whose first two crimes (or strikes) were stealing $10.00 and a bus pass, then
robbing a man on the street. Fourteen years later, he was caught attempting to
break into a church to steal food (his third strike). He received a sentence of
25 years to life. Even first strike sentences can be tough as evidenced by the
case of a Ms. Renée Bojé who has no criminal record. Currently living in
Vancouver, she is facing a minimum of 10 years in prison for watering a
marijuana plant on a balcony in California should she return to the U.S. (Anderssen,
1999).

A major justification

2
of mandatory prison sentencesis
that they will teach offenders that punishment is certain and severe, and thus
that "crime does not pay". In other words, this policy is largely
based upon the assumption that certain prison terms specifically deter
offenders. In this light, the current paper empirically examines the specific
deterrence hypothesis. Our primary concern is with offenders whose criminal
history or offense type is serious enough to warrant imprisonment. The schools
of thought on the validity of the specific deterrence hypothesis as it relates
to the use of prison are reviewed. Then, we present new evidence that directly
tests the notion that prison sentences punish or deter future offending.

Before proceeding, it is important to clarify what is meant by punishment.
While the terms "deterrence" and "punishment" are often used
interchangeably, our preference is to use the behavioural definition of
"punishment": the suppression of behaviour by response-dependent
events (Blackman, 1995). Note that this definition is purely functional. It
avoids common sense interpretations of what constitutes punishment, which are
often based on gut-level and moral philosophical grounds, and may, therefore, be
fallacious

3
(Matson & DiLorenzo, 1984).

Effects of Imprisonment: Three Schools of Thought

There are three schools of thought regarding the ability of prisons to
punish. The first is that prisons definitely suppress criminal behaviour. The
second perspective, the "schools of crime" viewpoint, proposes just
the opposite, that is, that prisons increase criminality. The third, which we
label the "minimalist/interaction" position, contends that the effects
of prison on offenders is, with few exceptions, minimal.

We review the basic assumptions of each school, present the best evidence in
support of their views and provide a brief critique of the merits of their
position.

Prisons as punishment

The view that the experience of prison in itself acts as a deterrent is
rooted in the simple specific deterrence theory (Andenaes, 1968) which predicts
that individuals experiencing a more severe sanction are more likely to reduce
their criminal activities in the future. Economists have taken the lead in
support of the specific deterrence model (see von Hirsch, Bottoms, Burney, &
Wikström, 1999). They maintain that incarceration imposes direct and indirect
costs on inmates (e.g., loss of income, stigmatization) (Nagin, 1998; Orsagh
& Chen, 1988; Pyle, 1995; Wood & Grasmick, 1999). Thus, faced with the
prospect of going to prison or after having experienced prison life, the
rational individual would choose not to engage in further criminal activities.
In addition, another "cost" argument, identical to that which the
"schools of crime" advocates employ (see next section), is that, if
prison life is a degrading, dehumanizing experience then it surely must be
regarded as an additional "psychological" cost of doing time.

Surveys indicate that both the public and offenders consider prison to be the
most severe or effective punisher of criminal behaviour (Doob, Sprott, Marinos,
& Varma, 1998; Spelman, 1995; van Voorhis, Browning, Simon, & Gordon,
1997).

4
Policy makers often assume that prison is the severest punishment available
(Wood & Grasmick, 1999). DeJong (1997) remarked that the expectations of the
public and policy-makers are that incarceration has powerful deterrent effects.

What kind of data is used to support the prison as punishment hypothesis? The
most persuasive evidence comes from some ecological studies where the results
are based on rates or averages (aggregate data).

An example of one of the most positive results came
from a study by Fabelo (1995) that reported a 30% increase in incarceration
rates across 50 U.S. states, corresponding with a decrease of 5% in the crime
rate for a five-year period.5
Fabelo’s data has been interpreted as convincing evidence that prisons punish
(Reynolds, 1996).

Some caveats about the potency of the prisons as punishers school should be
noted. Not all researchers view the ecological evidence regarding prisons as
convincing (Gendreau & Ross, 1981; von Hirsch et al., 1999). It must be
emphasized that ecological studies, based as they are on aggregate data, may say
absolutely nothing about individual behaviour (Andrews & Bonta, 1994; Menzel,
1950; Robinson, 1950). Furthermore, the effects found in aggregate studies,
which are expressed in correlational terms, are almost invariably wildly
inflated

In addition, Nagin (1998), who feels strongly that the deterrence literature
in general is persuasive, despairs that if the rate of imprisonment keeps
climbing, prisons will be seen as less stigmatizing thereby neutralizing any
possible deterrence effect. Others suggest that only some classes of offenders
may be deterrable, such as those who are more strongly bonded to society (i.e.,
at lower risk) (see DeJong, 1997). Orsagh and Chen (1988) have posited a U
-shaped threshold theory for the punishing event, by which a
"moderate" dosage of prison would be optimal. And, there is the
current view that the modern prison is too comfortable; only
"no-frills" prisons offer enough punishment to act as an effective
deterrent (Corcoran, 1993; Johnson, Bennett, and Flanagan, 1997). As in days
gone by, prisons should be places of only bare bones necessities,

7
where life is lived in fear (e.g., caning is appropriate) (Nossiter, 1994).

Schools of crime

The belief that prisons are "schools of crime" also has widespread
support. The earliest writings on crime by scholars such as Bentham, De Beaumont
and de Tocqueville, Lombroso and Shaw, suggested that prisons were breeding
grounds for crime (see Lilly, Cullen, & Ball, 1995). Jaman, Dickover, and
Bennett (1972) put the matter succinctly by stating that "the inmate who
has served a longer amount of time, becoming more prisonised in the process, has
had his tendencies toward criminality strengthened and is therefore more likely
to recidivate than the inmate who has served a lesser amount of time" (p.
7). This viewpoint is widely held today by many criminal justice professionals
and policy makers (see Cayley, 1998; Latessa & Allen, 1999; J. Miller, 1998;
Schlosser, 1998; Walker, 1987), some politicians (e.g., Clark, 1970; Rangel,
1999, who said that prisons granted Ph.D.s in criminality), and segments of the
public (Cullen, Fisher, & Applegate, in press). Aspects of our popular
culture (e.g., cinema) also reinforce the notion that prisons are mechanistic,
brutal environments that likely increase criminality (Mason, 1998).

How might prisons enhance criminality? There is a large body of literature of
primarily an anecdotal, qualitative, and phenomenological nature, which asserts
that the prisonisation process destroys the psychological and emotional
well-being of inmates (see Bonta & Gendreau, 1990; Cohen & Taylor,
1972). In contrast to the prisons as punishment view, "schools of
crime" advocates view the glass as half-full rather than half-empty. By
their reasoning, if prison psychologically destroys the inhabitants, then their
adjustment to society upon release can only be negative, with one likely
consequence being a return to crime.

A more precise specification of the mechanisms involved comes from
behavioural analysts. These researchers pay less heed to putative
psychologically destructive features of the prison environment, rather, they
focus simply on which beliefs and behaviours are reinforced or punished therein.
Bukstel and Kilmann’s (1980) classic review of the effects of prison
literature summarized several studies (e.g., Buehler, Patterson, & Furniss,
1966) that employed behavioural technologies to examine and record in detail the
social learning contingencies that existed in various prisons. Bukstel and
Kilmann (1980, p. 472) claimed that each study found "overwhelming positive
reinforcement" by the peer group for a variety of antisocial behaviours, so
much so, that even staff interacted with the inmates in a way that promoted a
procriminal environment. As with the phenomenological literature, the inference
here is that prisons should promote criminality.

8

Although the literature remains sparse, studies do exist which have
correlated the psychological changes offenders undergo in prison with their
recidivism upon release. Importantly, the findings from this research are not
consistent with the "schools of crime" position (see Gendreau, Grant,
& Leipciger, 1979; Wormith, 1984; Zamble & Porporino, 1990). Many of the
coping behaviours or psychological changes seen among prisoners are not
predictive of recidivism, and only a few are correlated with changes in
recidivism.

Minimalist/interaction school

Different frames of reference have contributed to this perspective. The first
three coalesce nicely to provide compelling reasons why prisons should have no
appreciable effect on recidivism. There is the human and animal experimental
learning and behaviour modification literatures (see Gendreau, 1996). Coupled
with the social psychology of persuasion knowledge base, they provide ample
evidence to refute the notion that it is an easy matter to coerce offenders.
Furthermore, the offender personality literature attests to the fact that the
makeup of offenders is a complicating factor. We address each in turn.

Firstly, there has been a tremendous amount of research on which punishing
events are the most effective in suppressing behaviour (Matson & DiLorenzo,
1984). Prison life events are not included among them. In addition, there are
several absolutely crucial criteria that must always apply in order for
punishment to be maximally effective (Schwartz & Robbins, 1995). Some of
these are that the punishing stimuli must be immediate, as intense as possible,
predictable, and the delivery of punishment serves as a signal that
reinforcement is not available for the punished response. Given the nature of
these strictures, it has been noted that "it is virtually impossible to
meet these criteria in the real world in which offenders live unless some
unbelievably efficient Orwellian environment" (Gendreau, 1996, p. 129)
exists akin to a giant Skinner box. Others who have examined this issue have
come to a similar conclusion (e.g., Clark, 1995; J. McGuire, 1995; Moffitt,
1983). Furthermore, and this is a critical point, punishment only trains a
person what not to do. If one punishes a behaviour what is left to replace it?
In the case of high-risk offenders, simply other antisocial skills! This is why
punishment scholars state that the most effective way to produce behavioural
change is not to suppress "bad" behaviour, but to shape
"good" behavior (e.g., Blackman, 1995).

Also, the road travelled from committing a crime to incarceration is
circuitous given that only a "tiny fraction" of criminal
victimizations result in prison time, in most cases, months later (Bennett,
DiIulio, & Walters, 1996, p. 49). And, offenders’ knowledge of sanctions,
even of highly publicised ones (e.g., Bennett, et al., 1996; Jaffe, Leschied,
& Farthing, 1987), is far from accurate.

Secondly, the social psychology literature on persuasion and resistance
processes provides another compelling rationale as to why at least the threat of
punishment, such as prison, is decidedly problematic. This is a complex
literature which deserves a fuller analysis; suffice it to say, that for
persuasion to occur the principle of positive reciprocity (i.e., do something
nice to somebody) must apply. The source of the message must be credible,
attractive, and authoritative (but not authoritarian), and the appeal of the
message engineered so that commitment on the part of the receiver is achieved (Cialdini,
1993; W. J. McGuire, 1995). Once commitment has occurred, several other steps
must be met in order for behaviour to change (Fishbein, 1995).

9
Additionally, clinicians who are skilled in breaking down resistance to change
express empathy, avoid argumentation, support self-efficacy, and do not
excessively confront or threaten (Miller & Rollnick, 1991). To repeatedly
threaten someone is to invite the well-documented process of psychological
inoculation whereby individuals think of reasons to resist change (see Eagly
& Chaiken, 1993). We suspect that offenders are masters of this behaviour. A
study by Hart (1978) of punishment in the army is a good example of the
occurrence of the inoculation principle.

Thirdly, the question must be asked as to who the criminal justice system
wishes to punish. The salient beliefs and attitudes of higher risk offenders,
whom one most wishes to change, are antagonistic to education, employment, and
supportive interpersonal relationships. Their personalities can be highly
egocentric, manipulative, and impulsive. They frequently engage in skewed
decision-making processes that greatly over-estimate the benefit of antisocial
actions vs. the costs involved (see Andrews & Bonta, 1998; Carroll, 1978;
Gendreau, Little, & Goggin, 1996; Gendreau & Ross, 1981; Hare, 1996).

10
They may often be under the influence of a substance thereby further distorting
their perceptions of reality. Some would agree that the nature of offenders is
such that they may be resistant to punishment even under circumstances where
optimal punishment conditions apply (see Andrews & Bonta, 1998, p. 171-173;
Gendreau & Suboski, 1971).

Taken together, these three sets of literature suggest that the effects of
prison are likely minimal. A closely allied view is that the effects of
imprisonment are conditional, that while prisons generally have little effect on
offenders, there are exceptions to the rule. Originally, researchers from this
camp came into the field with the expectation that prisons were "schools of
crime" only to conclude from their work and the available evidence that
prisons were basically "psychological deep freezes" (Zamble &
Porporino, 1988). In essence, they were stating that the behaviour seen in
prison was similar to that which existed prior to incarceration. Cross-sectional
and longitudinal studies of length of incarceration and differential prison
living conditions have found few negative psychological results of incarceration
(Bonta & Gendreau, 1990; Gendreau & Bonta, 1984); in fact, in some areas
the opposite result has occurred (see Zamble, 1992, and the special edition of
the Canadian Journal of Criminology, October 1984 volume 26, on the
effects of incarceration). Offenders, moreover, who have been the most
anti-social in prison and the most likely to recidivate upon release, have also
tended to be higher risk going into prison (Gendreau, Goggin, & Law, 1997).

Despite this overall trend, these researchers left room for some interactions
to occur (e.g., Bonta & Gendreau, 1990; Paulus & Dzindolet, 1993;
Wright, 1991) by asking the questions what types of offenders under which prison
living conditions might be adversely affected (Bonta & Gendreau, 1990, p.
366). For example, Zamble and Porporino (1990) found the higher risk
incarcerates coped the least well in prison. They suggest that they could be
prone to a greater degree of recidivism. On the other hand, a commonly expressed
view is that it is low-risk offenders for whom prison has the greater negative
impact. Leschied and Gendreau (1994) contended, on the basis of aggregate
recidivism trends in Canada and a social learning model of criminal behaviour
(Andrews & Bonta, 1998), that incarcerated low risk offenders should be
negatively influenced by the potent antisocial values of their higher risk peers
(also see Feldman, Caplinger, & Modarsky, 1983; Leschied, Jaffe, &
Austin, 1988). Higher risk offenders should be little influenced by a term of
imprisonment.

In summary, the three schools of thought make different predictions about the
effect of prison on recidivism. They are:

1. Prisons as punishment: prisons reduce recidivism. This effect may be
moderated by individual and situational factors. Lower risk offenders may be
more readily deterred and prisons with fewer "frills" (e.g., studies
conducted in prisons decades earlier) might produce better results. Length of
sentence may also be a factor.

2. Schools of crime: prisons increase recidivism for all offenders.

3. Minimalist/Interaction: the effect prisons have on recidivism are minimal
at best; some offenders (lower or higher risk) may fare worse.

As this review has noted, however, the data in support of each school is
inconclusive in that it cannot be a substitute for an analysis of the effects of
prison on the recidivism of individual offenders. Fortunately, there exists a
heretofore neglected literature which directly addresses the aforementioned
hypotheses (Bonta & Gendreau, 1992; Levin, 1971; Song & Lieb, 1993).
These authors provided narrative reviews of studies which compared the
recidivism rates of offenders who were incarcerated for differing lengths of
time as well as offenders incarcerated vs. those sentenced to a community
sanction. The conclusions reached were tentative because of the small number of
studies assessed (

» a
dozen studies).11

The problem with narrative reviews is that they lack precision. Conclusions
are often couched in terms of imprecise qualitative (e.g., "more" or
"less") judgements. They are subjective and open to bias, as evidence
is sometimes used selectively to support a favoured theory or ideology (see
Rosenthal, 1991). In the last decade meta-analytic techniques have supplanted
the traditional narrative review as the gold standard for assessing results
across studies in medicine and the social sciences in a more precise, objective
fashion (Hunt, 1997).

Meta-analysis summarizes a collection of individual studies in a quantitative
fashion. That is, the findings from each study are pooled and statistically
analysed. The end result is a precise, quantitative summary of the magnitude of
the effect within a particular body of literature. In addition, meta-analysis
examines the extent to which the characteristics of combined studies (e.g.,
quality of research design, nature of the subjects, etc.) are related to the
magnitude of the effect size.

This study, therefore, attempts to build upon previous narrative reviews by
expanding the literature search

12
and employing meta-analytic techniques to determine the precise effect of
prisons on recidivism.

Method

13

Sample of Studies

A literature search for studies examining the effects of time in prison on
recidivism was conducted using the ancestry approach and library abstracting
services. For a study to be included, data on the offender had to be collected
prior to the recording of the recidivism results. A minimum follow-up period of
six months was required. The study was also required to report sufficient
information to calculate a correlation between the "treatment"
condition (e.g., prison vs. no prison) and recidivism. This correlation is the
phi coefficient (

Phi coefficients (f ) were produced for all
treatment - control comparisons in each study that reported a numerical
relationship with recidivism. The following is an example of what the f
value represents in a particular case where the respective recidivism rates for
a group of offenders imprisoned for 5 years vs. 3 years were 30% vs. 25%
respectively. The f value was .05, the exact
difference between the recidivism rates of the two comparison groups. The reader
will note that the f value is a very practical effect
size indice and easy to interpret. Unless there are extreme base rates and the
sample sizes in the comparison groups vary greatly, the f
value represents the exact difference (or fall within 1 or 2 percentage points)
in recidivism between two comparison groups (Cullen & Gendreau, in press).

In the event of non-significant predictor-criterion relationships, where a p
value of greater than .05 was the only reported statistic, a f
of .00 was assigned.

Next, the obtained correlations were transformed into a weighted f
value (z±) that takes into account the sample size
of each effect size and the number of effect sizes per sanction. (Hedges &
Olkin, 1985). The weighting was done because some would argue that more credence
should be given to effect sizes with larger sample sizes. Please note that
outcome was recorded such that a positive f or z±
is indicative of an unfavourable result (i.e., the stronger the sanction - more
prison time - the higher the recidivism rate).

Effect Size Magnitude

The assessment of the magnitude of the effect of various sanctions on
recidivism was conducted by examining the mean values of f
and z± and their respective confidence intervals (CI).
The CI is the 95% probability that the interval contains the population
value. If the CI does not include 0 it can be concluded that the mean
effect size is significantly different from 0 (i.e, better than chance alone).
If there is no overlap between the CIs, then the conditions being
compared are assessed as statistically different from one another at the .05
level.

Results

Description of the Studies

More vs. Less Time in Prison

Twenty-three studies examining the effect of more vs. less time in prison met
the criteria for inclusion and generated 222 effect sizes with outcome.

14

All of the studies in the sample were published, either in journals, texts,
or government reports. More than 90% of the effect sizes came from American
studies, the majority of which were conducted during the 1970s (86%). The data
set included a substantial range in the number of effect sizes reported per
study (n = 1 - 79) and the distribution of sample sizes across effect
sizes (n = 19 - 1,608).

Ninety-eight percent of effect sizes were generated from adult samples, the
majority of them male (90%). Race was not specified for the majority of effect
sizes (75%). Level of risk by effect size was evenly distributed between samples
assessed as low (49%) versus high risk (49%). Determination of risk rarely
involved the use of valid standardized psychometrics (16%). Rather, for most
effect sizes, it was deduced from either the number of prior offences within the
sample (47%) or the reported percentage of recidivism of the comparison group at
study completion (36%).

A measure of study design quality found that just over half of the effect
sizes in the more vs. less domain came from studies rated as strong in design
(55%). These were studies where the more vs. less groups were similar on at
least five risk factors. The period of follow-up for almost two-thirds of effect
sizes was between six months and one year (64%). The most common type of outcome
among this group of effect sizes was parole violation (77%).

Incarceration vs. Community-Based

A total of twenty-seven studies met the criteria for inclusion in the
incarceration vs. community-based domain, reporting 103 effect sizes with
recidivism. Offenders in the latter category were under various probation or
parole conditions.

As with the more vs. less data set, here too all of the studies involved were
published and the majority of effect sizes came from American studies (68%),
while 22% were generated from studies conducted in the United Kingdom. Overall,
the effect sizes herein were representative of more recently produced studies
(96% published since 1980). While the number of effect sizes per study was
relatively discrete (n = 1 - 12), there was considerable range in sample
sizes associated with effect sizes (n = 24 - 54,633).

Sixty-eight percent of effect sizes were generated from adult samples, with
23% coming from juveniles. Regardless of age, the majority of effect sizes
involved males (62%). Race was not indicated for half the effect sizes (50%).
Almost two-thirds of effect sizes were associated with offenders considered at
high risk to re-offend (59%). Risk designation was most commonly determined from
the number of prior offences within the sample (61%). Among a minority of effect
sizes, risk was calculated using a valid standardized psychometric (23%).

Within the incarceration vs. community domain, study design quality was rated
as weak for a majority of effect sizes (62%). For almost two-thirds of the
effect sizes length of follow-up was between one year and three years (65%). The
distribution of type of outcome was evenly split among arrest (22%), conviction
(32%), and incarceration (30%).

Effects on Recidivism

Spending more vs. less time in prison or being incarcerated vs. remaining in
the community was associated with slight increases in recidivism for 3 of 4
outcomes. These results are detailed in Table 1 which can be read in the
following manner. Beginning with the first row, one sees that there were 222
comparisons of groups of offenders who spent more vs. less time in prison. Of
these 222 comparisons, 190 recorded the approximate time in months spent in
prison. The average length of incarceration for the "more" and
"less" groups was 30.0 months vs. 12.9 months respectively (footnote
a, Table 1).

15
The total number of offenders involved in these comparisons was 68,248. The mean
unweighted effect size was f
= .03, equivalent to a 3% increase in recidivism (29% vs. 26%) for those
offenders who spent more time in prison. The confidence interval (CI) was
.03 to .05. When the effect sizes were weighted by sample size, the z±
was the same (.03) and it’sCI was .02 to .04.

In the case of the incarceration vs. community comparison, the data showed a
7% increase in recidivism (49% vs. 42%)

16
or a f = .07, for those
offenders who were imprisoned. Upon weighting, the effect size became .00. The
amount of time spent incarcerated could not be reliably determined (»
10.5 months) as only 19 of 103 comparisons reported this information.

Combining the results for the two types of sanctions in Table 1 produced a
mean

f of .04 (CI
= .03 to .06) and a z± of .02 (CI =
.02 to .02).

Effects of Incarceration by Risk Level

The more vs. less results presented in Table 1 were sub-divided by risk
categories.

17
Of the more vs. less comparisons, 139 were designated as high risk and 78 as low
risk. There was a tendency for the lower risk groups to show a greater increase
in recidivism.

In the higher risk group, those who spent more time in prison had a higher
recidivism rate (3%) than did their counterparts who spent less time in prison (

f
= .03, CI = .01 to .05). Once weighted, the z±
was .02 with a CI = .01 to .03.

In the lower risk group, those who spent a longer time in prison had a higher
(4%) recidivism rate than those who spent less time in prison (

f
= .04, CI = .01 to .06). Upon weighting, the z±
was .05 with a CI = .04 to .06.

In the incarceration vs. community comparison, 69 of the samples were
classified as high risk and 25 as low risk. Differences in recidivism rate were
virtually identical, whether measured in terms of

f
or z±, and were
almost identical within each risk group or between high and low risk categories.

Correlation between Length of Time Difference Score and Recidivism by Risk
Level

Another type of analysis of the risk issue was carried out in the following
manner. First, the difference in the amount of time served in months was
tabulated for each of the more vs. less comparison groups. Of the 190 effect
sizes, 124 were classed as high risk and 66 as low risk. Then, within each of
the high and low risk groups, the correlation between the amount of time served
in months and recidivism was computed.

Table 2 shows that more time served was positively correlated with higher
recidivism rates (

f )
for the high risk group (r = .22) and the low risk (r = .15). The CIs
of both groups, however, overlapped.When effect sizes were weighted by
sample size, the relationship between time served and recidivism (z±)
was higher for the lower risk group (r = .29) than
the higher risk (r = .17). Again, the CIs overlapped.

Other Comparisons

Length of incarceration was grouped into three levels: (a) Time 1 - less than
1 year, (b) Time 2 - more than 1 year and less than 2 years, and (c) Time 3 -
more than 2 years. No evidence was found to support a U-shaped relationship
between the three time periods and recidivism (Time 1 - % recidivism = 28.2, CI
= 24.5 to 31.8; Time 2 - % recidivism = 26.8, CI = 24.8 to 28.8; and Time
3 - % recidivism = 24.1, CI = 21.2 to 26.9, respectively). Note that the CIs
for all three time periods overlapped considerably.

The relationship of selected study characteristics

18
to f was examined within
each of the more vs. less and incarceration vs. community sanctions. In the case
of the former, none were found to be related to effect size.

With respect to the latter, there were four significant comparisons. Mean
effect sizes were significantly greater among studies whose quality of research
design was rated as higher quality (

f
= .11, CI = .09 to .14) vs. lower quality (f
= .04, CI = .01 to .08), indicating an increase in recidivism among
offenders from well-designed studies. In addition, mean effect sizes were also
higher among studies which determined offender risk using valid, psychometric
protocols (f = .14, CI
= .10 to .18) or where it was deduced from the control group’s recidivism rate
(f = .12, CI =
.05 to .18) than those where risk level had to be decided on the basis of the
presence or absence of a criminal history among the offenders (f
= .03, CI = .00 to .06).

For this same group, effect sizes also differed by length of follow-up, such
that those followed for 1 to 3 years had higher mean effect size (

f
= .10, CI = .08 to .13) than did either those followed for less than 1
year (f = -.01, CI
= -.05 to .03) or those followed for more than 3 years (f
= .03, CI = -.03 to .08). Mean f
values also differed by type of outcome. Both incarceration (f
= .13, CI = .09 to .16) and court contact (f
= .17, CI = .03 to .31) were associated with significantly higher mean
effects than arrest (f =
.01, CI = -.02 to .04).

Discussion

The data in this study represents the only quantitative assessment of the
relationship between time spent in prison and offender recidivism. The database
consisted of 325 comparisons involving 336,052 offenders. On the basis of the
results, we can put forth one conclusion with a good deal of confidence. None of
the analysis conducted produced any evidence that prison sentences reduce
recidivism. Indeed, combining the data from the more vs. less and incarceration
vs. community groupings resulted in 4% (

f
) and 2% (z±) increases
in recidivism.

In addition, the results provided no support for three other hypotheses. The
prediction that recidivism rates correlate with sentence length in a U-shaped
fashion was not supported. The view that only lower risk offenders would be
deterred by prison sentences was also not confirmed. The lower risk group who
spent more time in prison had higher recidivism rates.

The hypothesis that "no frills" prisons would be better at
punishing criminal behaviour was tested indirectly. The most consistently
negative results came from the more versus less group, albeit, one should note
that the majority of these effect sizes came from prison studies of

»
30 years ago, a time when prisons were noted for being barren, harsh
environments (f = .03; z±
= .03 with neither CIs including 0).

Other results emanating from this research must be approached with
considerably more caution because of the nature of the database. The studies
reviewed contained precious little information on essential features.
Descriptions of the offender samples were cursory and inconsistent (e.g.,
determinations of risk) across studies. Typical of other prison literatures
(e.g., Gendreau et al., 1997), virtually nothing was known about the prisons
themselves (i.e., how they were managed, existence of treatment programs, etc.)
Many of the results from the more vs. less group came from studies of prison
samples from the 1950 to 1970 era, when fewer amenities were prevalent, and from
relatively few jurisdictions in one country, the U.S. Additional studies
representative of this decade and other countries are urgently required.

19
Therefore, we regard the trend in the findings that prisons are even modest
schools of crime (i.e., marginally worse results for lower risk offenders in 3
of 4 statistical comparisons) as tentative.

Before addressing any policy implications forthcoming from the study some
comments are in order about the equivalence of the comparison groups. It is
often assumed that if a study does not have a true experimental design (i.e.,
random assignment) then the integrity of the results may somehow be diminished.
In other words, non-random designs are presumed to report greatly inflated
results. Recent meta-analyses encompassing

In this study pre-post designs were excluded. Only comparison group designs
were included in the analysis after being categorized as to higher or lower
quality. The higher quality group comparisons, in our view, were comprehensive
given that the experimental and control groups did not differ on at least 5
important risk factors (i.e., criminal history, substance abuse, etc.), and,
moreover, many of the comparisons were based on validated risk measures. Where
some demographic differences between groups were reported, the results were
statistically adjusted to account for these discrepancies. Interestingly, within
the incarceration vs. community domain, the higher quality studies reported
higher recidivism rates for the incarcerated group! There were no differences in
effect size by design quality for the more vs. less category. Finally, two
effect sizes came from randomized designs; they reported 5% and 9% increases in
recidivism for the incarceration group.

What are the possible policy implications emanating from this study? There
are, in our view, two viable recommendations. Prisons should not be used with
the expectation of reducing future criminal activity. If further research
supports the findings described herein, that time in prison increases offender
recidivism by even "small" amounts, then the costs accruing from the
excessive use of prison could be enormous. For example, even percentage changes
of approximately 5% have resulted in significant cost implications in medicine
and other areas of human services (Hunt, 1997). In the criminal justice field it
is estimated that the criminal career of just one high-risk offender
"costs" approximately $1,000,000 (see Cohen, 1997). Arguably,
increases in recidivism of even a "fractional" amount are not fiscally
responsible, especially given the high incarceration rates currently in vogue in
North America. One should also bear in mind that even the most enthusiastic
proponents of the utility of sanctions are not only quite sceptical about the
use of prison but state, in no uncertain terms, that the deterrence literature
in general is of limited use in formulating public crime control policy (Nagin,
1998).

20

Therefore, the primary justification for use of prisons is incapacitation and
retribution, both of which come with a "price", if prisons are used
injudiciously. Locking up chronic high risk offenders for a reasonable period of
time is not under debate; we can think of no one who disagrees with that policy.
In order to lock up enough prisoners, however, to reduce crime rates by a few
percentage points (see Gendreau & Ross, 1981) and to make prisons
"pay" for themselves (DiIulio & Piehl, 1991), substantial
"costs" will accrue to other government ministries or departments.
Unless an infinite source of funds becomes available to governments, fewer
expenditures will be directed to education and health care, amongst other
things. As a case in point, money spent by states to keep inmates incarcerated
recently has risen by 30% while spending on higher education dropped by 19%, and
costs to keep a child in school represent a quarter of that required to lock up
an offender (Dobbin, 1999).

As for retribution, what appears to be a conceptually straightforward notion
is, in fact, very complex. Walker (1991) has studied the justifications for
retribution in considerable detail and has concluded that many retributive lines
of reasoning are confounded by utilitarian objectives or run afoul of moral
positions.

21

Our second recommendation attests to the sad reality that so little is known
about what goes on inside the "black box" of prisons and how this
relates to recidivism (Bonta & Gendreau, 1990). Only a mere handful of
studies have attempted to address this matter (Gendreau et al., 1979; Zamble
& Porporino, 1990). Analogously, could one imagine so ubiquitous and costly
a procedure in the medical or social services fields receiving such cursory
research attention?

If a fuller appreciation of the effect of time in prison on recidivism is
ever to be gained, then it is incumbent upon prison systems to do the following.
They must continuously assess the situational factors that can mediate their
institutional climates (i.e., inmate turnover, see Gendreau et al., 1997) and
have a potentially negative impact on prisoners’ adjustment and, possibly, a
long-term effect on recidivism. Appropriate measures are available for this
purpose (e.g., Wright, 1985).

Secondly, it is necessary to conduct periodic assessments of prisoners (e.g.,
every six months to a year) on a wide variety of dynamic risk factors using
valid risk protocols.

22
While we await further confirmation, it is particularly important to closely
monitor the progress of lower risk offender while incarcerated. This type of
clinical information gathering will provide us with a much more sensitive and
precise estimate of the effects of prison time that did the data available to us
in this study. Only then will prison managers be able to empirically determine
which offenders are more prone to recidivating upon release. With such knowledge
in hand something truly constructive can be done (e.g., treatment, surveillance)
to minimize risk to the public.

Footnotes

1. The opinions expressed are solely those of the authors. Preparation of
this report was supported by contract #9914-GE/587 from the Solicitor General of
Canada. We thank Mike Bradley, Murray Goddard and Travis Pitt for their
assistance in the preparation of this document.

2. The recent evidence concerning the consequences of mandatory sentencing
for the justice system has been alarming (see Caulkins, Rydell, Schwabe, &
Chiesa, 1997; Crutchfield, Bridges, & Pitchford, 1994; Dobbin, 1999; Greider,
1998; Tonry, 1998; Wooldredge, 1996). Prison populations have tripled nationwide
over the last 20 years and increased fivefold in the federal prison system
alone. The U.S. Justice Department’s budget has increased from $4 to $21
billion in 12 years. Courts are being clogged as defendants are more likely to
insist on trial. Rand researchers’ econometric analyses estimated that
$1,000,000 spent on mandatory sentences would result in a reduction in drug
consumption (i.e., cocaine) of only 13 kilograms, while spending the same amount
on treatment would see a corresponding reduction in drug consumption of 100
kilograms. Discretion has moved from the hands of judges to prosecutors with the
latter being possibly less accountable. Across 90 federal jurisdictions that are
responsible for administering mandatory sentencing policies, discrepancies in
prison time meted out for similar offenses vary by a ratio of 10:1.

Some of the factors influencing the administration of mandatories in various
localities are race, public fear of crime, media influences, type of drugs used,
cultural values, prosecutorial caseloads, the use of informants, and
idiosyncratic interpretation of the legal process. It is claimed that these
inequities erode public trust in laws, moreover, hypocrisy flourishes as some
prosectors and judges "bend the rules" to avoid what are perceived as
blatant injustices. Finally, the evidence to date indicates that mandatory
sentences have had little effect on aggregate crime rates (Stolzenberg & D’Alessio,
1997).

3. Common sense definitions often run into difficulty because they cavalierly
assume

something must be painful. In reality, some events, while not intuitively
obviously aversive, may be effective punishers and vice-versa. Here is a
fascinating "real world" example; on the basis of common sense, some
U.K. prison authorities thought that they had designed a truly
"punishing" regime, only to discover that the prisoners found some of
the activities reinforcing (Thornton, Curran, Grayson, & Holloway, 1984)!

4. The survey data can be complex. The Doob et al., (1998) study found that
the public showed some inconsistencies; while endorsing prison as an effective
deterrent, over 70% opted for money not to be spent on prisons but on non-prison
alternatives (e.g., prevention and rehabilitation). Cullen, Fisher, &
Applegate (in press) have found considerable support for rehabilitation even
within conservative areas in the U.S. Spelman (1995) and Wood and Grasmick
(1999) reported that some offenders (

»
30%) would prefer a brief period of incarceration (one year or less) to
extensive community sanctions.

5. Fabelo’s (1995) data can be expressed in terms of a simple correlation
between incarceration rates and crime rates. It is r = -.41.

6. An example of how aggregate data analysis tends to inflate results in the
criminal

justice field can be seen in Hsieh & Pugh’s (1993) report that the
correlation between two indices of social class and violent crime was r =
.44, whereas, individual level data analyses report a much smaller relationship
of r = .07 (Gendreau, Little, & Goggin, 1996).

8. Bukstel & Kilmann were not inferring that all prisons have to function
in this manner, and nor are we (see also Andrews & Bonta, 1998). It is
reasonable to suggest, however, that the majority of staff in many prisons are
not selected, trained, supervised and rewarded principally for their ability to
develop and maintain pro-social attitudes and behaviour amongst inmates with the
ultimate goal of reducing recidivism. Secondly, extremely few prisons have
generated evidence that they have been successful in rehabilitating offenders
(see Gendreau, 1996 for references to those that have).

9. From Fishbein (1995) these steps are: the environment in which the
offender lives has no chance of reinforcing the behaviour to be changed. The
offender has a positive attitude towards performing the behaviour, believes the
benefits outweigh the costs, and the behaviour is consistent with his
self-image. Finally, not only should the offender believe he/she can perform the
behaviour in a variety of life situations but actually has the skills to do so.

10. There are all kinds of interesting contradictions regarding offenders’
thoughts about risk of apprehension which is not surprising given offenders’
personality make-up. For example, in one survey, the majority of offenders
claimed that prison was a deterrent while maintaining that they did not deserved
to be punished and that society was definitely no safer with them in prison (Van
Voorhis, et al. 1997). Risk of apprehension applies more to others or is simply
dismissed (Claster, 1967; Wright & Decker, 1994). Offenders who are more
likely to offend in the future had higher risk perceptions of being caught (Horney
& Marshall, 1992). While 75% of young offenders did not know the penalties
that applied to them, 90% felt they were well-informed and disagreed with the
law anyway (Jaffe et al., 1984).

11. There have also been a few single studies that examined such a large
number of comparisons (e.g., Gottfredson, Gottfredson, & Garofalo, 1977)
that, without a quantitative assessment, it was impossible for the authors to
precisely determine the direction and magnitude of the results.

12. The search did not include boot camp studies which are a form of
specialised military "treatment" (Gendreau, Goggin, & Fulton, in
press).

13. For a complete description of the methods, statistics and a list of
studies employed in the meta-analysis please contact the first author at gendreau@unbsj.ca
or by faxing 506-648-5780.

14. Some studies report several effect sizes by comparing differing lengths
of prison terms. For example, a study could report recidivism rates for
offenders serving 1, 3, or 5 years, thereby offering the comparison of any of
the inherent combinations, for a total of three effect sizes (i.e., 1 vs. 3, 1
vs. 5, etc.).

15. These figures are approximate. They represent an underestimation in the
"more" category as studies sometimes reported sentences at the upper
end as 24 months+, with no limit to the upper end. At the lower end studies
reported the range of time served within limits (e.g., 6 - 12 months) which we
scored at the midpoint.

16. The recidivism rates were higher for this category because the studies in
this data set reported longer follow-up periods. Most of the more vs. less
effect sizes were associated with short follow-up periods of 6 months to 1 year.

17. Offender risk designation was determined on the basis of the studies
having reported prior record among the offender samples, a low risk designation
equating with no priors. In the absence of any description of prior record in
the original studies, the authors used one of the following criteria to
designate risk: the level of risk based on the results of a valid risk measure
as reported in the study, or the recidivism rates of the comparison group were
used to determine risk (low risk = a recidivism rate of 15% in the first year of
follow-up or 30% during a follow-up of two years or more).

18. Study characteristics whose frequency distributions were not skewed
(i.e., no value > 60% of the distribution) were selected for further
analysis. These included study decade, offender age, offender risk level, risk
assessment methodology, quality of research design, type of control group,
length of follow-up, and type of outcome.

19. Why there are so few current studies that correlate length of
incarceration with recidivism of offenders of similar risk level is puzzling.
There has to be a wealth of data which could address this issue in today’s
prisons.

20. Assume for a moment that future research finds some offenders to be
deterred by longer prison sentences or a brief period of incarceration.
Psychological theory predicts they would be those offenders who were more
introverted, less psychopathic, etc., in other words, those of lower risk
(Andrews & Bonta, 1998, p. 171-173). Can one imagine a justice system,
operating under the principles of fairness, invoking a utilitarian policy that
meted out more severe sentences to lower risk offenders even though they may
have committed crimes of similar nature and severity as their higher risk
counterparts?

21. Walker (1991) contends (p. 139) that the most logically consistent
argument retributivists can assert is the right to have retributive feelings.

22. For a list of some of the most useful risk measures see Gendreau, Goggin,
and Paparozzi (1996). It is known that changes in offender risk level are
predictive of meaningful shifts in recidivism (i.e.,

Nagin, D. S. (1998). Criminal deterrence research at the outset of the
twenty-first century. In M. Tonry (Ed.), Crime and justice: A review of
research Vol. 23 (pp. 1-42). Chicago, IL: University of Chicago Press.

Nossiter, A. (1994, September 17). Making hard time harder: States cut jail
TV and sports. New York Times, pp. A1, A10.

Orsagh, T., & Chen, J.-R. (1988). The effect of time served on
recidivism: An interdisciplinary theory. Journal of Quantitative Criminology,
4, 155-171.

Correlation between Length of Prison Time Difference Score and Effect Size by
Risk Classification

(k)

N

Difference

r

1

CI

1

r

2

CI

2

Incarceration: More vs. Less

1. High Risk (124)

44,415

17.3

.22

.05 to .39

.17

.00 to .34

2. Low Risk (66)

20,919

16.9

.15

-.09 to .39

.29

.07 to .51

3. Total (190)

68,248

17.2

.20

.06 to .34

.21

.07 to .35

Note.

Difference = Mean difference in length
of time served in months between the "More" and "Less"
groups; r1
= correlation between the mean Length of Prison Time Difference score and f
; CI1
= confidence interval about r1;
r2
= correlation between the mean Length of Prison Time Difference score and z±;
CI2 =
confidence interval about r2.